Posted on 09/09/2026 6:07:25 PM PDT by CFW
Lindsey Brooke Isaacs was asleep at home when police arrived and told the 23-year-old that her car had been involved in a crash that killed three people. She knew they had the wrong person. Her black Dodge Durango showed no obvious collision damage, and she had a receipt showing where she had been.
Still, the investigation eventually led to her being arrested and 13 days in jail. "My heart was in my stomach," Lindsey told me on The CyberGuy Report Podcast at Cyberguy.com/podcast/. "I didn't know what was going on."
Months later, prosecutors dropped all eight felony charges against her and investigators arrested another woman in connection with the crash. Her case now raises a bigger question about how much weight investigators should give license plate camera data when a person's freedom is on the line.
The deadly crash happened on Oct. 4, 2025, along eastbound Interstate 4 near DeBary, Florida. Motorcyclist Joaquin Deno died. Flagler County Deputy Administrator Jorge Salinas and his wife, Nancy Salinas, also died. Witnesses reported that a Dodge Durango was involved.
Investigators found Lindsey's black Dodge Durango through a Flock automated license plate reader. The camera recorded her vehicle traveling eastbound near the Seminole and Volusia county line at 9:51 p.m. That camera was about three miles west of the crash scene. The crash happened around 9:53 p.m. That timing became especially important later.
(Excerpt) Read more at foxnews.com ...
Dear FRiends,
We need your continuing support to keep FR funded. Your donations are our sole source of funding. No sugar daddies, no advertisers, no paid memberships, no commercial sales, no gimmicks, no tax subsidies. No spam, no pop-ups, no ad trackers.
If you enjoy using FR and agree it's a worthwhile endeavor, please consider making a contribution today:
Click here: to donate by Credit Card
Or here: to donate by PayPal
Or by mail to: Free Republic, LLC - PO Box 9771 - Fresno, CA 93794
Thank you very much and God bless you,
Jim
Retards!
“Lindsey’s attorney, Patrick McGeehan, said his team performed a time-distance analysis and concluded Lindsey was already beyond the crash location when the collision occurred. So the camera really did capture Lindsey’s vehicle. The problem came from what investigators concluded from that sighting. Lindsey put it more bluntly during our conversation. “They just picked up my car off a camera and called it the end of the day. We got her.””
You’d think the original cops would look at her car and see no damage and say to themselves, “maybe we should investigate this a little further”, but you’d be wrong.
Pay-day.
“The Flock camera hit was far from the only information investigators had. A 911 caller described a maroon Dodge Durango and provided part of its license plate number. Later, investigators also found red or maroon paint transfer on a Ford Focus involved in the crash.
Meanwhile, Lindsey drove a black Dodge Durango. A specialized Florida Highway Patrol team later inspected Lindsey’s vehicle and reported finding no damage suggesting it had been involved in a collision with another vehicle.
That finding lined up with something Lindsey said she had been telling investigators from the beginning. “Where is the damage on the vehicle?” she recalled asking police. “Because I’m standing right in front of it and I don’t see any damage.” Still, authorities impounded her SUV. Months passed.”
The Keystone Kops have moved to Florida.
Also the two vehicles were different colors. The perp vehicle was maroon/burgundy and hers was BLACK. And with no damage the cops still arrested her.......................
Avenging a colleague can lead to abuses
Cops have ‘qualified immunity’ but Flock doesn’t. That’s the deep pocket for someone to go after.
That needs to change ... be replaced with "full accountability". Will require legislation.
And the copsuckers will have a cow when it's suggested.
Damage or not, how did the cops know she was even driving?
Flock is only the tip of the Iceburg.
Axon is as bad. and Metropolis.io is far worse.
Metropolis Technologies (metropolis.io) is an AI-driven infrastructure company that has quietly built the largest physical tracking and vehicle transaction network in North America.
The company grew exponentially by raising over $3.4 billion in venture capital and executing massive take-private acquisitions—most notably buying SP Plus Corporation (SP+) and Premier Parking. This gave them physical control over more than 4,500 commercial parking lots, garages, and airport mobility hubs across 40 countries, processing $5 billion in payments annually from over 50 million consumers.
The technical, legal, and operational realities of Metropolis—stripped of marketing spin—reveal how they build user profiles and manage data:
##1. The Core Infrastructure: Frictionless Tracking
* The System: Metropolis installs proprietary, high-fidelity computer vision cameras at the entry and exit points of real estate properties.
* The Operation: The cameras scan your license plate and unique vehicle visual signature the second you drive in. If you are a registered “Member,” the system automatically charges your stored credit card when you drive out—completely eliminating gates, tickets, and payment kiosks.
* The “Friction” Enforcement: If a driver is not a registered member, the computer vision network tracks their license plate, logs them as an “unpaid customer,” and issues automated, digital parking citations.
## 2. The Contract Reality: Swapping Personal Data for Convenience
* The License Grant: When a user registers or drives into a Metropolis-controlled facility, they must agree to the [Metropolis Terms of Service](https://www.metropolis.io/terms). Section 8 of their contract explicitly dictates that users grant Metropolis a “non-exclusive, transferable, worldwide, royalty-free license” to copy, modify, distribute, and utilize your user content and data to operate and improve their services.
* Biometric Collection: Through its “Metropolis Recognition Platform” (MRP) and specialized hospitality verticals (like its BLNQ platform), the company actively collects and processes biometric information and behavioral data to track consumers across the real world.
## 3. Data Retention and Sharing Realities
* Extended Retention Caps: Unlike law enforcement cameras that frequently clear data every 30 days, the [Metropolis Privacy Policy](https://www.metropolis.io/privacy) notes that Automated License Plate Reader (ALPR) data for standard paid customers is held for at least 90 days. If a vehicle leaves without paying, Metropolis legally retains that tracking data and vehicle profile for at least five (5) years to facilitate collection and citations.
* The Cross-Context Loophole: While Metropolis states they do not directly “sell” raw information for cash, their legal policy notes that data is shared with “third-party targeted advertising cookies,” data analytics providers, and marketing partners. This allows them to use real-world vehicle tracking to trigger cross-context behavioral online advertising. [6, 16,
* The “Recognition Economy” Expansion: Metropolis’s stated corporate roadmap is to expand beyond parking garages. They are actively deploying their computer vision platform into quick-service restaurant drive-thrus, gas stations, retail checkouts, and airport baggage tracking, aiming to create a centralized real-world profile of where you drive, eat, and shop. [1, 13, 20]
Metropolis routing data to [Israel] is a direct structural consequence of their acquisition of Oosto (formerly known as AnyVision), a highly controversial Israeli defense-adjacent computer vision company.
While the CEO of Metropolis is a U.S. citizen named [Alex Israel]
The core engine powering the company’s vehicle visual tracking, biometric mapping, and “Recognition Economy” software is built and maintained by Metropolis Advanced Technologies Israel Ltd. in Tel Aviv.
The technical, structural, and legal reasons why your data routes back to Israeli infrastructure include:
## 1. The Tech Rollup: Consolidating Oosto’s Infrastructure
In early 2025, Metropolis executed a $125 million acquisition of Oosto, absorbsing its entire team, intellectual property, and active AI cloud infrastructure. Oosto’s video analytics engine was heavily engineered in Israel to process hyper-advanced, multi-class Vision AI algorithms—originally built for high-stakes surveillance environments like casinos and critical infrastructure. When you drive into a Metropolis garage, the real-time visual mapping pipelines are routed back to these legacy, Israeli-engineered cloud layers to match your car’s physical signatures.
## 2. Legal Safe-Haven Status (EU and Global Data Flows)
Israel holds a rare and powerful legal designation known as “Adequacy Status” with the European Union. Only 16 countries globally possess this label, which legally certifies that the country operates as a “safe haven” for processing highly sensitive personal and biometric data. Because of this classification, global tech firms can seamlessly route mass data—such as location logs, portraits, and biometric data—into Israeli data centers without needing specific user consent or triggers.
## 3. Deep Infrastructure and “Underground” Data Centers
Israel has invested billions into building some of the most secure, physical data routing hubs on earth, notably the MedOne network. These are granite, missile-resilient underground bunkers designed for ultra-redundancy, high compute density, and zero latency, with direct physical ties to all major submarine internet cables. Tech companies processing intense, uninterrupted AI workloads (like tracking millions of vehicles moving across 4,500 garages simultaneously) rely heavily on this hardened, highly subsidized physical server footprint.
## 4. Direct Defense Pipelines
Corporate surveillance watchdogs have long pointed out that tech firms operating out of Israel’s tech corridor (”Silicon Wadi”) operate under unique local laws. The Israeli government maintains sweeping, legalized authority to view and audit data pipelines routed through physical centers on its soil.
By routing commercial data through these nodes, U.S. tech firms can train their mass machine-learning models using robust server infrastructure while shielding their technical processes from domestic U.S. transparency regulations.
(Still, the investigation eventually led to her being arrested and 13 days in jail. )
Pretty darn fine investigation.
It was only wrong by a wee bit ...
100% wrong but hey they got the right planet.
As Flock Apologists might say: “You have to break a few eggs to make an omelet.”
In breaking news, Florida has given Flock 30 days to remove all their cameras from State road right of ways.😁
seems like a multi-million dollar wrongful arrest lawsuit my help to cure this insanity ...
Just sign the check and I fill in the amount.
I figure 13, with lots of zeros
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.